Daniel W. Bearden

A 12-week feeding trial with juvenile red drum (Sciaenops ocellatus) fed high-soybean meal (SBM) diets was conducted to investigate a putative biomarker of nutritional imbalance, N-formimino-L-glutamate (FIGLU). Three fishmeal-free, 60% SBM pelleted diets (named B12, Fol, and Met, respectively) were tested to evaluate the effects on growth performance and tissue metabolite profiles of supplementation of vitamin B₁₂ (0.012 mg/kg), folate (10 mg/kg), methionine (1 g/kg) respectively, above basal supplementation levels. A fourth SBM-based diet (named B12/Fol/Met) was formulated with a combination of B₁₂, folate, and methionine to attain the above-mentioned target concentrations. A fifth 60% SBM diet (named FWS) with methionine supplementation (1 g/kg above basal supplementation levels), enriched with taurine, lysine and threonine as well as minerals, was also tested. This diet contained formulation targets and additives which have allowed for replacing fishmeal with plant proteins in rainbow trout feeds. Control diets included a fishmeal-based diet (named FM), an unsupplemented basal 60% SBM diet (named SBM60), and a “natural” diet (named N) made up of equal parts of fish (cigar minnows), squid and shrimp as a positive reference for growth performance. Formulated feeds contained approximately 37% total crude protein, approximately 14% total crude lipid and were energetically balanced. Standard growth performance metrics were measured, and tissues (liver, muscle) were collected at week 12 to evaluate diet-induced metabolic changes using nuclear magnetic resonance (NMR)-based metabolomics. Our results show that the FWS diet outperformed all other SBM diets and the FM diet under all performance metrics (P < 0.05). FIGLU was not detected in fish fed the N diet but was detected in those fed the SBM diets and the FM diet. Fish fed the FWS diet and the Met diet showed lower hepatic levels of FIGLU compared with the other SBM-based diets (P < 0.05), suggesting that among the different supplementation regimes, methionine supplementation was associated with lower FIGLU levels. The FWS diet produced tissue metabolite profiles that were more similar to those of fish fed the N diet. Based on our results, the FWS diet constitutes a promising SBM-based alternative diet to fishmeal for red drum.

There is a lack of experimental reference materials and standards for metabolomics measurements, such as urine, plasma, and other human fluid samples. Reasons include difficulties with supply, distribution, and dissemination of information about the materials. Additionally, there is a long lead time because reference materials need their compositions to be fully characterized with uncertainty, a labor-intensive process for material containing thousands of relevant compounds. Furthermore, data analysis can be hampered by different methods using different software by different vendors. In this work, we propose an alternative implementation of reference materials. Instead of characterizing biological materials based on their composition, we propose using untargeted metabolomic data such as nuclear magnetic resonance (NMR) or gas and liquid chromatography-mass spectrometry (GC-MS and LC-MS) profiles. The profiles are then distributed with the material accompanying the certificate, so that researchers can compare their own metabolomic measurements with the reference profiles. To demonstrate this approach, we conducted an interlaboratory study (ILS) in which seven National Institute of Standards and Technology (NIST) urine Standard Reference Material^®s (SRM^®s) were distributed to participants, who then returned the metabolomic data to us. We then implemented chemometric methods to analyze the data together to estimate the uncertainties in the current measurement techniques. The participants identified similar patterns in the profiles that distinguished the seven samples. Even when the number of spectral features is substantially different between platforms, a collective analysis still shows significant overlap that allows reliable comparison between participants. Our results show that a urine suite such as that used in this ILS could be employed for testing and harmonization among different platforms. A limited quantity of test materials will be made available for researchers who are willing to repeat the protocols presented here and contribute their data.

We describe here the agreed upon first development steps and priority objectives of a community engagement effort to address current challenges in quality assurance (QA) and quality control (QC) in untargeted metabolomic studies. This has included (1) a QA and QC questionnaire responded to by the metabolomics community in 2015 which recommended education of the metabolomics community, development of appropriate standard reference materials and providing incentives for laboratories to apply QA and QC; (2) a 2-day ‘Think Tank on Quality Assurance and Quality Control for Untargeted Metabolomic Studies’ held at the National Cancer Institute’s Shady Grove Campus and (3) establishment of the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) to drive forward developments in a coordinated manner.

Recent progress in metabolomics has been aided by the development of analysis techniques such as gas and liquid chromatography coupled with mass spectrometry (GC-MS and LC-MS) and nuclear magnetic resonance (NMR) spectroscopy. The vast quantities of data produced by these techniques has resulted in an increase in the use of machine algorithms that can aid in the interpretation of this data, such as principal components analysis (PCA) and partial least squares (PLS). Techniques such as these can be applied to biomarker discovery, interlaboratory comparison, and clinical diagnoses. However, there is a lingering question whether the results of these studies can be applied to broader sets of clinical data, usually taken from different data sources. In this work, we address this question by creating a metabolomics workflow that combines a previously published consensus analysis procedure ( https://doi.org/10.1016/j.chemolab.2016.12.010 ) with PCA and PLS models using uncertainty analysis based on bootstrapping. This workflow is applied to NMR data that come from an interlaboratory comparison study using synthetic and biologically obtained metabolite mixtures. The consensus analysis identifies trusted laboratories, whose data are used to create classification models that are more reliable than without. With uncertainty analysis, the reliability of the classification can be rigorously quantified, both for data from the original set and from new data that the model is analyzing.

We investigated the metabolic effects of four different commercial soy-based protein products on red drum fish (Sciaenops ocellatus) using nuclear magnetic resonance (NMR) spectroscopy-based metabolomics along with unsupervised principal component analysis (PCA) to evaluate metabolic profiles in liver, muscle, and plasma tissues. Specifically, during a 12 week feeding trial, juvenile red drum maintained in an indoor recirculating aquaculture system were fed four different commercially available soy formulations, containing the same amount of crude protein, and two reference diets as performance controls: a 60% soybean meal diet that had been used in a previous trial in our lab and a natural diet. Red drum liver, muscle, and plasma tissues were sampled at multiple time points to provide a more accurate snapshot of specific metabolic states during the grow-out. PCA score plots derived from NMR spectroscopy data sets showed significant differences between fish fed the natural diet and the soy-based diets, in both liver and muscle tissues. While red drum tolerated the inclusion of soy with good feed conversion ratios, a comparison to fish fed the natural diet revealed that the soy-fed fish in this study displayed a distinct metabolic signature characterized by increased protein and lipid catabolism, suggesting an energetic imbalance. Furthermore, among the soy-based formulations, one diet showed a more pronounced catabolic signature.

Cancer-associated thrombocytosis has long been linked to poor clinical outcome, but the underlying mechanism is enigmatic. We hypothesized that platelets promote malignancy and resistance to therapy by dampening host immunity. We show that genetic targeting of platelets enhances adoptive T cell therapy of cancer. An unbiased biochemical and structural biology approach established transforming growth factor β (TGFβ) and lactate as major platelet-derived soluble factors to obliterate CD4⁺ and CD8⁺ T cell functions. Moreover, we found that platelets are the dominant source of functional TGFβ systemically as well as in the tumor microenvironment through constitutive expression of the TGFβ-docking receptor glycoprotein A repetitions predominant (GARP) rather than secretion of TGFβ per se. Platelet-specific deletion of the GARP-encoding gene Lrrc32 blunted TGFβ activity at the tumor site and potentiated protective immunity against both melanoma and colon cancer. Last, this study shows that T cell therapy of cancer can be substantially improved by concurrent treatment with readily available antiplatelet agents. We conclude that platelets constrain T cell immunity through a GARP-TGFβ axis and suggest a combination of immunotherapy and platelet inhibitors as a therapeutic strategy against cancer.

We conducted a 16‐wk feeding trial with large juvenile red drum, Sciaenops ocellatus. Four diets were randomly assigned to six replicate tanks per treatment. Three isonitrogenous (ca. 44.5% protein) and isolipidic (ca. 14.1% lipid) extruded diets were formulated to compare a fishmeal‐based diet with diets using alternative protein sources. Diet 1 contained 19.60% fishmeal and 21.42% poultry meals as primary protein sources. Two alternative diets were formulated reducing the fishmeal to 0.61% by substituting poultry meals (33.85%) and soybean protein concentrate (11.55% in Diet 2 and 11.70% in Diet 3). Diet 3 also included Allzyme Vegpro® and Allzyme® SSF at 0.04%. Diet 4, a natural diet consisting of chopped cigar minnows, squid, and shrimp, was used as a positive control to compare growth rates of formulated feeds to near maximum growth under these culture conditions. We found that reducing the amount of fishmeal to <1% by using alternative protein sources did not affect the growth rate, survival, or health of red drum but improved assimilation of phosphorus, reduced potential release of P to the environment, and significantly lowered the amount of feeder fish needed in feed. The control diet identified performance benchmarks for future feeds development work.

Introduction The Metabolomics Society Data Quality Task Group (DQTG) developed a questionnaire regarding quality assurance (QA) and quality control (QC) to provide baseline information about current QA and QC practices applied in the international metabolomics community. Objectives The DQTG has a long-term goal of promoting robust QA and QC in the metabolomics community through increased awareness via communication, outreach and education, and through the promotion of best working practices. An assessment of current QA and QC practices will serve as a foundation for future activities and development of appropriate guidelines. Method QA was defined as the set of procedures that are performed in advance of analysis of samples and that are used to improve data quality. QC was defined as the set of activities that a laboratory does during or immediately after analysis that are applied to demonstrate the quality of project data. A questionnaire was developed that included 70 questions covering demographic information, QA approaches and QC approaches and allowed all respondents to answer a subset or all of the questions. Result The DQTG questionnaire received 97 individual responses from 84 institutions in all fields of metabolomics covering NMR, LC-MS, GC-MS, and other analytical technologies. Conclusion There was a vast range of responses concerning the use of QA and QC approaches that indicated the limited availability of suitable training, lack of Standard Operating Procedures (SOPs) to review and make decisions on quality, and limited use of standard reference materials (SRMs) as QC materials. The DQTG QA/QC questionnaire has for the first time demonstrated that QA and QC usage is not uniform across metabolomics laboratories. Here we present recommendations on how to address the issues concerning QA and QC measurements and reporting in metabolomics.